Create README.md

README.md

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+---
+pipeline_tag: image-text-to-text
+inference: false
+license: apache-2.0
+---
+
+<br>
+<br>
+
+# LLaVA-Reasoner Model Card
+
+## Model details
+
+**Model type:**
+LLaVA-Reasoner is an open-source image vision language model, fine-tuned from GPT4-o distilled chain-of-thought (CoT) reasoning data. 
+
+This model is the **SFT** version, with additional math data compared to SFT-preview.
+
+Base LLM: [Lin-Chen/open-llava-next-llama3-8b](https://huggingface.co/Lin-Chen/open-llava-next-llama3-8b)
+
+**Model date:**
+Trained on Sep, 2024.
+
+**Paper or resources for more information:**
+
+Paper: https://arxiv.org/abs/2410.16198
+
+Code: https://github.com/RifleZhang/LLaVA-Reasoner-DPO/tree/main
+
+## License
+[Lin-Chen/open-llava-next-llama3-8b](https://huggingface.co/Lin-Chen/open-llava-next-llama3-8b) license.
+
+**Where to send questions or comments about the model:**
+https://github.com/RifleZhang/LLaVA-Reasoner-DPO/issues
+
+## Intended use
+**Primary intended uses:**
+Image CoT reasoning
+
+**Primary intended users:**
+Researchers in artificial intelligence, large multimodal model, etc.
+
+## Training dataset
+[ShareGPT4o-Reasoning](https://huggingface.co/datasets/Share4oReasoning/sft_data) dataset.
+
+## Evaluation
+Follow https://github.com/RifleZhang/LLaVA-Reasoner-DPO/blob/main/README.md
+
+
+## citation
+```
+@article{zhang2024improve,
+  title={Improve vision language model chain-of-thought reasoning},
+  author={Zhang, Ruohong and Zhang, Bowen and Li, Yanghao and Zhang, Haotian and Sun, Zhiqing and Gan, Zhe and Yang, Yinfei and Pang, Ruoming and Yang, Yiming},
+  journal={arXiv preprint arXiv:2410.16198},
+  year={2024}
+}
+```